IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v493y2018icp342-358.html
   My bibliography  Save this article

Thermodynamic properties of diamond and wurtzite model fluids from computer simulation and thermodynamic perturbation theory

Author

Listed:
  • Zhou, S.
  • Solana, J.R.

Abstract

Monte Carlo NVT simulations have been performed to obtain the thermodynamic and structural properties and perturbation coefficients up to third order in the inverse temperature expansion of the Helmholtz free energy of fluids with potential models proposed in the literature for diamond and wurtzite lattices. These data are used to analyze performance of a coupling parameter series expansion (CPSE). The main findings are summarized as follows, (1) The CPSE provides accurate predictions of the first three coefficient in the inverse temperature expansion of Helmholtz free energy for the potential models considered and the thermodynamic properties of these fluids are predicted more accurately when the CPSE is truncated at second or third order. (2) The Barker–Henderson (BH) recipe is appropriate for determining the effective hard sphere diameter for strongly repulsive potential cores, but its performance worsens with increasing the softness of the potential core. (3) For some thermodynamic properties the first-order CPSE works better for the diamond potential, whose tail is dominated by repulsive interactions, than for the potential, whose tail is dominated by attractive interactions. However, the first-order CPSE provides unsatisfactory results for the excess internal energy and constant-volume excess heat capacity for the two potential models.

Suggested Citation

  • Zhou, S. & Solana, J.R., 2018. "Thermodynamic properties of diamond and wurtzite model fluids from computer simulation and thermodynamic perturbation theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 493(C), pages 342-358.
  • Handle: RePEc:eee:phsmap:v:493:y:2018:i:c:p:342-358
    DOI: 10.1016/j.physa.2017.10.016
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437117310269
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2017.10.016?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:493:y:2018:i:c:p:342-358. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.